National Public Health Dashboards: Protocol for a Scoping Review.

BACKGROUND: The COVID-19 pandemic highlighted the importance of robust public health data systems and the potential utility of data dashboards for ensuring access to critical public health data for diverse groups of stakeholders and decision makers. As dashboards are becoming ubiquitous, it is imperative to consider how they may be best integrated with public health data systems and the decision-making routines of diverse audiences. However, additional progress on the continued development, improvement, and sustainability of these tools requires the integration and synthesis of a largely fragmented scholarship regarding the purpose, design principles and features, successful implementation, and decision-making supports provided by effective public health data dashboards across diverse users and applications. OBJECTIVE: This scoping review aims to provide a descriptive and thematic overview of national public health data dashboards including their purpose, intended audiences, health topics, design elements, impact, and underlying mechanisms of use and usefulness of these tools in decision-making processes. It seeks to identify gaps in the current literature on the topic and provide the first-of-its-kind systematic treatment of actionability as a critical design element of public health data dashboards. METHODS: The scoping review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The review considers English-language, peer-reviewed journal papers, conference proceedings, book chapters, and reports that describe the design, implementation, and evaluation of a public health dashboard published between 2000 and 2023. The search strategy covers scholarly databases (CINAHL, PubMed, Medline, and Web of Science) and gray literature sources and uses snowballing techniques. An iterative process of testing for and improving intercoder reliability was implemented to ensure that coders are properly trained to screen documents according to the inclusion criteria prior to beginning the full review of relevant papers. RESULTS: The search process initially identified 2544 documents, including papers located via databases, gray literature searching, and snowballing. Following the removal of duplicate documents (n=1416), nonrelevant items (n=839), and items classified as literature reviews and background information (n=73), 216 documents met the inclusion criteria: US case studies (n=90) and non-US case studies (n=126). Data extraction will focus on key variables, including public health data characteristics; dashboard design elements and functionalities; intended users, usability, logistics, and operation; and indicators of usefulness and impact reported. CONCLUSIONS: The scoping review will analyze the goals, design, use, usefulness, and impact of public health data dashboards. The review will also inform the continued development and improvement of these tools by analyzing and synthesizing current practices and lessons emerging from the literature on the topic and proposing a theory-grounded and evidence-informed framework for designing, implementing, and evaluating public health data dashboards. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52843.

Public health intervention amidst conflict: Violence, politics, and knowledge frames in the 2018-20 Ebola epidemic in Democratic Republic of the Congo.

Research, policy, and donor interest in health systems in conflict environments has grown rapidly in recent years. The 2018-20 Ebola outbreak in Democratic Republic of the Congo is a critical case of healthcare militarization. The first-ever such outbreak in an active conflict zone, it grew notorious for violence against response teams, with attacks aggravating the spread of disease. However, while medical responders observed physical attacks, the causes of the violence remained largely unknown. Drawing on interviews and participant observation, we contribute civilian vantages of the way health intervention grew militarized, or associated with conflict. The argument builds in two core steps. A first reconstructs civilian experiences of conflict prior to Ebola to trace how the response took on a political meaning. We find that relationships linking state forces with the health response inadvertently tethered Ebola to what civilians perceived as security threats and that by repeating government statements about conflict, response teams unintentionally endorsed a version of the truth that silenced local voices. A second step addresses a central paradox: residents communicated these concerns directly, repeatedly, and via official response channels, yet healthcare teams failed to apply these insights. We locate this gap in the knowledge structures, or frames, accompanying intervention. Medical emergencies in warzones operate with dual sets of frames casting conflict players as "non-state" and public health resistance as "ignorance." Both frames intersect in ways that amplify invisibilities in each, clouding understandings of the nature of conflict and humanitarians' role in it. We suggest this places intervention teams at heightened risk of mis-stepping on political fault lines-and not understanding why. The study advances work on community engagement by showing that instead of simply providing scientific knowledge, effective engagement requires adjusting socio-political lenses within the response. It contributes to studies on health intervention, humanitarian emergencies, and the limits of medical neutrality.

REDCap to Epic interfaces create an efficient hybrid software solution for a public health registry.

A public health registry and intervention was created in response to the Flint water crisis to identify and refer exposed individuals to public health services to ameliorate the deleterious impact of lead exposure. Traditional technology architecture domains, funded scope of work, as well as community input were considered when defining the requirements of the selected solutions. A hybrid software solution was created using Research Electronic Data Capture (REDCap) to deploy an open participant survey and bypass requirements to create user accounts, and Epic to manage deduplication and participant communication and tracking. To bridge the two software systems, REDCap to Epic unidirectional ADT and Documentation Flowsheet interfaces were built to automate creation of subject records in Epic identical to those created in REDCap and to copy key protocol-driving variables from REDCap to Epic. The interfaces were critical to deliver a successful hybrid solution in which the desired features of each software could be leveraged to satisfy specific protocol requirements and community input. Data from the start of survey administration (December 2018) through 31 December 2020 are reported to demonstrate the usefulness of the interfaces.

Trust in public health policy in the time of the COVID-19 epidemic in Israel.

The government of Israel provides universal health care through four health care organizations ("sick funds") that enjoy general public trust. In hindsight, the response of the government to the COVID-19 epidemic seems reasonable. In the first year of the epidemic, tests and vaccines were developed and other measures were taken, including social distancing, focusing on risk factors for infection and disease severity, and improving treatment. The COVID-19 mortality rate between January 2000 and June 2021 was around 750 per million inhabitants, well below the OECD average of 1300. Still, although the control measures were largely well received, the media and an ad hoc non-governmental Emergency Council for the coronavirus crisis in Israel criticized the government's response to the epidemic thereby contributing to a decline in public trust in government policy. This commentary provides an overview of the importance of trust in medical institutions and the difficulties of evaluating healthcare decisions in an attempt to justify three conclusions. First, when physicians and self-appointed experts publicly disapprove of a government policy, they should consider the trade-off between improving care and undermining public trust. Second, when evaluating a medical decision, experts should not ask, "Would I have acted differently?" but rather, "Was the decision under review completely unreasonable?" Thirdly, criticism is certainly worth listening to. However, I believe that by calling for organized resistance against the government, the publicly announced establishment of the Emergency Council for the Corona crisis blatantly crossed the line between constructive criticism and destructive mistrust.

Public Health Responses to CBRN Terrorism in the Middle East and North Africa.

OBJECTIVE: Escalating global challenges (such as disasters, conflict, and climate change) underline the importance of addressing Chemical, Biological, Radiological, and Nuclear (CBRN) terrorism for sustainable public health strategies. This study aims to provide a comprehensive epidemiological analysis of CBRN incidents in the Middle East and North Africa (MENA) region, emphasizing the necessity of sustainable responses to safeguard healthcare infrastructures. METHOD: Utilizing a retrospective approach, this research analyzes data from the Global Terrorism Database (GTD) covering the period from 2003 to 2020. The study focuses on examining the frequency, characteristics, and consequences of CBRN incidents in the MENA region to identify patterns and trends that pose significant challenges to public health systems. RESULTS: The analysis revealed a significant clustering of CBRN incidents in Iraq and Syria, with a predominant involvement of chemical agents. These findings indicate the extensive impact of CBRN terrorism on healthcare infrastructures, highlighting the challenges in providing immediate health responses and the necessity for long-term recovery strategies. CONCLUSIONS: The study underscores the need for improved healthcare preparedness, robust emergency response systems, and the development of sustainable public health policies. Advocating for international collaboration, the research contributes to the strategic adaptation of healthcare systems to mitigate the impacts of CBRN terrorism, ensuring preparedness for future incidents in the MENA region and beyond.

The Need to Widen the Concept of Health and to Include the Spiritual Dimension.

For many, the World Health Organization's (WHO) definition of health does not reflect their own understanding of health, because it lacks aspects such as spiritual wellbeing. Responding to these concerns, the WHO called in 2023 for a vision of health that integrates physical, mental, psychological, emotional, spiritual, and social wellbeing. To date, medical practitioners are often reluctant to consider spiritual aspects, because of a perceived lack of statistical evidence about the strength of relations. Research on this topic is emerging. A recent study among 800 young people living with HIV in Zimbabwe showed how study participants navigated three parallel, at times contradicting health systems (religious, traditional, medical). Conflicting approaches led to multifaceted dilemmas (= spiritual struggles), which were significantly related to poorer mental and physical health. This illustrates the need for inclusion of spiritual aspects for health and wellbeing in research, and of increased collaboration between all stakeholders in healthcare.

Community Voices and Whole-Genome Sequencing for Tuberculosis: Storytelling and the Importance of Listening.

One of the primary public health functions of a tuberculosis (TB) program is to arrest the spread of infection. Traditionally, TB programs have relied on epidemiological information, gathered through contact tracing, to infer that transmission has occurred between people. The ability of drawing such inferences is extensively context dependent. Where epidemiological information has been strong, such as 2 cases of TB occurring sequentially within a single household, confidence in such inferences is high; conversely, public health authorities have been less certain about the significance of TB cases merely occurring in the same wider social group or geographic area. Many current laboratory tests for TB used globally may be sufficient to confirm a diagnosis and guide appropriate therapy but still be insufficiently precise for distinguishing two strains reliably. In short, drawing inferences regarding a chain of transmissions has always been as much art as science.

A reproducible ensemble machine learning approach to forecast dengue outbreaks.

Dengue fever, a prevalent and rapidly spreading arboviral disease, poses substantial public health and economic challenges in tropical and sub-tropical regions worldwide. Predicting infectious disease outbreaks on a countrywide scale is complex due to spatiotemporal variations in dengue incidence across administrative areas. To address this, we propose a machine learning ensemble model for forecasting the dengue incidence rate (DIR) in Brazil, with a focus on the population under 19 years old. The model integrates spatial and temporal information, providing one-month-ahead DIR estimates at the state level. Comparative analyses with a dummy model and ablation studies demonstrate the ensemble model's qualitative and quantitative efficacy across the 27 Brazilian Federal Units. Furthermore, we showcase the transferability of this approach to Peru, another Latin American country with differing epidemiological characteristics. This timely forecast system can aid local governments in implementing targeted control measures. The study advances climate services for health by identifying factors triggering dengue outbreaks in Brazil and Peru, emphasizing collaborative efforts with intergovernmental organizations and public health institutions. The innovation lies not only in the algorithms themselves but in their application to a domain marked by data scarcity and operational scalability challenges. We bridge the gap by integrating well-curated ground data with advanced analytical methods, addressing a significant deficiency in current practices. The successful transfer of the model to Peru and its consistent performance during the 2019 outbreak in Brazil showcase its scalability and practical application. While acknowledging limitations in handling extreme values, especially in regions with low DIR, our approach excels where accurate predictions are critical. The study not only contributes to advancing DIR forecasting but also represents a paradigm shift in integrating advanced analytics into public health operational frameworks. This work, driven by a collaborative spirit involving intergovernmental organizations and public health institutions, sets a precedent for interdisciplinary collaboration in addressing global health challenges. It not only enhances our understanding of factors triggering dengue outbreaks but also serves as a template for the effective implementation of advanced analytical methods in public health.

Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic.

The substance use disorder epidemic has emerged as a serious public health crisis, presenting complex challenges. Visual analytics offers a unique approach to address this complexity and facilitate effective interventions. This paper details the development of an innovative visual analytics dashboard, aimed at enhancing our understanding of the substance use disorder epidemic. By employing record linkage techniques, we integrate diverse data sources to provide a comprehensive view of the epidemic. Adherence to responsive, open, and user-centered design principles ensures the dashboard's usefulness and usability. Our approach to data and design encourages collaboration among various stakeholders, including researchers, politicians, and healthcare practitioners. Through illustrative outputs, we demonstrate how the dashboard can deepen our understanding of the epidemic, support intervention strategies, and evaluate the effectiveness of implemented measures. The paper concludes with a discussion of the dashboard's use cases and limitations.

A synthesis of evidence for policy from behavioural science during COVID-19.

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

Unleashing the global potential of public health: A framework for future pandemic response.

Public health emergencies, especially pandemics, need to be managed globally, and on several levels, emphasizing the importance of leadership, communication, and synchronization of measures, data, and management plans in contrast to the management of the Coronavirus-19 pandemic, which illustrated diverse strategies employed by various nations. This paper aims to review and discuss whether globalized diseases in a globalized world should be managed by globalized public health. Using a systematic literature search, followed by a non-systematic literature review, selected studies were grouped into topics, and analyzed, using content analysis to enhance the conclusive results. The results present a roadmap towards a re-envisioned framework highlighting key areas of focus: data-driven decision-making, robust technology infrastructure, global cooperation, and ongoing public health education, as part of a coordinated global response. This article reveals the weaknesses of current pandemic management systems and recommends new steps to further strengthen the management of future pandemics.

Retention of Community Health Workers in the Public Health Workforce: Public Health Workforce Interests and Needs Survey, 2017 and 2021.

Objectives. To investigate the organizational factors contributing to the intent of community health workers (CHWs) to quit their jobs in local and state health departments in the United States. Methods. We used the 2017 (n = 844) and 2021 (n = 1014) Public Health Workforce Interests and Needs Survey data sets to predict CHWs' intent to leave with Stata 17 balanced repeated replication survey estimations. Results. CHWs dissatisfied with organizational support, pay, or job security had high probabilities of reporting an intent to leave (50%, P < .01; 39%, P < .01; and 42%, P < .01, respectively) relative to satisfied or neutral workers (24%, P < .01; 21%, P < .01; and 26%, P < .01, respectively). Conclusions. Improving organizational support, pay satisfaction, and job security satisfaction in public health agencies can significantly improve CHW retention, potentially lowering overall organizational costs, enhancing organizational morale, and promoting community health. Public Health Implications. Our findings shed light on actionable ways to improve CHW retention, including assessing training needs; prioritizing diversity, equity, and inclusion; and improving communication between management and workers. (Am J Public Health. 2024;114(1):44-47. https://doi.org/10.2105/AJPH.2023.307462).

Standard Occupational Classification Codes: Gaps in Federal Data on the Public Health Workforce.

Objectives. To determine whether US Department of Labor standard occupational classification (SOC) codes can be used for public health workforce research. Methods. We reviewed past attempts at SOC matching for public health occupations and then used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to match the actual job titles for 26 516 respondents to the 2021 Public Health Workforce Interests and Needs Survey (PH WINS) with SOC codes, grouped by respondents' choice of job category in PH WINS. We assessed the accuracy of the NIOCCS matches and excluded matches under a cutpoint using the Youden Index. We assessed the percentage of SOC matches with insufficient information and diversity of SOC matches per PH WINS category using the Herfindahl-Hirschman Index. Results. Several key public health occupations do not have a SOC code, including disease intervention specialist, public health nurse, policy analyst, program manager, grants or contracts specialist, and peer counselor. Conclusions. Without valid SOC matches and detailed data on local and state government health departments, the US Department of Labor's data cannot be used for public health workforce enumeration. (Am J Public Health. 2024;114(1):48-56. https://doi.org/10.2105/AJPH.2023.307463).

Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts.

How likely is it to become infected by SARS-CoV-2 after being exposed? Almost everyone wondered about this question during the COVID-19 pandemic. Contact-tracing apps1,2 recorded measurements of proximity3 and duration between nearby smartphones. Contacts-individuals exposed to confirmed cases-were notified according to public health policies such as the 2 m, 15 min guideline4,5, despite limited evidence supporting this threshold. Here we analysed 7 million contacts notified by the National Health Service COVID-19 app6,7 in England and Wales to infer how app measurements translated to actual transmissions. Empirical metrics and statistical modelling showed a strong relation between app-computed risk scores and actual transmission probability. Longer exposures at greater distances had risk similar to that of shorter exposures at closer distances. The probability of transmission confirmed by a reported positive test increased initially linearly with duration of exposure (1.1% per hour) and continued increasing over several days. Whereas most exposures were short (median 0.7 h, interquartile range 0.4-1.6), transmissions typically resulted from exposures lasting between 1 h and several days (median 6 h, interquartile range 1.4-28). Households accounted for about 6% of contacts but 40% of transmissions. With sufficient preparation, privacy-preserving yet precise analyses of risk that would inform public health measures, based on digital contact tracing, could be performed within weeks of the emergence of a new pathogen.